Abstract Despite efficient antiretroviral treatments (ART) HIV persists as latent genome primary in long-lived memory CD4 T cells. While a lot of efforts focus on identifying the most potent and safe LRAs to induce HIV re- expression, the processes leading to antigen expression, processing and epitope presentation -allowing latently infected cells to be revealed and targeted by the immune system- are still not understood. Productive infection occurs mostly in activated CD4 T cells while re-expression happens in non-activated memory CD4 T cell subsets and in the presence of ART and LRAs. We hypothesize that latency reversal induced by LRAs in CD4 T cells leads to specific conditions for both antigen expression and degradation into peptides that are different from those established during productive infection, altering the pool of degradation peptides displayed by CD4 T cells. Thus the impact of LRAs on the antigen processing machinery, specifically the capacity to generate a broad array of degradation peptides covering HIV antigens may contribute to the efficacy of immune detection and clearance of reactivated CD4 T cells. Our goal is to perform an antibody-independent, unbiased, ultrasensitive proteomic and peptidomic analysis to identify HIV-derived markers of latency reversal. We have developed mass spectrometry assays and computational tools to analyze the proteome, intracellular protein degradation products and MHC-bound peptidome of primary cells. We identified MHC-bound peptides from productively infected CD4 T cells, defining hot spots of peptide presentation that are surprisingly not in the most immunogenic areas of the proteome and may reveal new targets for immune clearance. We showed that various categories of LRAs affect cellular hydrolytic peptidase activities in different ways distinct from the modulations induced by CD3/28 activation of CD4 T cells, in line with changes in proteasome RNA expression upon LRA treatment identified by our collaborator. LRA-induced variations in peptidase activities modified degradation patterns, kinetics and amount of peptides produced. Using a new model of HIV latency developed by Drs Sekaly and Chomont that mimics latency and LRA- specific reactivation in memory CD4 T cell subsets we propose to 1) Identify HIV-derived products generated during productive infection vs. latency reversal, 2) Assess the capacity of latency reversal-specific CD8 T cells to clear reservoirs. To assess the relevance of our findings for in vivo latency we will compare our data on changes in antigen expression and processing to transcriptomics analysis Dr Sekaly's group generates in parallel with the latency model and ex vivo with cells from patients enrolled in clinical trials. This proposal builds on the expertise of the PI in antigen processing, together with Dr Heckerman for computational analysis, Dr Sekaly for the latency model in memory CD4 T cells and reservoir studies during latency reversal, and Dr Walker for clinical samples and CD8 T cell expertise.